Quantitative Analyst - Market Risk Quantitative Analyst - Market Risk …

Hamlyn Williams
in Amsterdam, Noord-Holland, Netherlands
Permanent, Full time
Last application, 20 Jan 20
Salary + Relocation
Hamlyn Williams
in Amsterdam, Noord-Holland, Netherlands
Permanent, Full time
Last application, 20 Jan 20
Salary + Relocation
Hamlyn Williams
An international banking client based in Amsterdam is looking for a VP level Quantitative Analyst to join their Market Risk Model Validation team with a focus on carrying out initial and periodic validation of all market risk models used within the bank. Particular focus is given to the Trading Risk and FRTB suite of models, whilst the team also covers all Counterparty Credit Risk, ALM, IRRBB, Liquidity Risk, Stress Testing and Operational Risk Models.

Role Responsibilities:

Initial and periodic validation of quant models
Quantitative analysis and review of model frameworks, assumptions, data, and results
Designing, modelling and prototyping challenger models when required
Testing models numerical implementations and reviewing documentations
Checking the adherence to governance requirements
Documentation of findings invalidation reports, including raising recommendations for model improvements
Ensuring models are validated in line with regulatory requirements and industry best practice
Tracking remediation of validation recommendations
Preparation of model risk reporting for Model Oversight Committee and Board

 

Essential

Ph.D. (Preferred) or MSc in a quantitative subject (Mathematics, Statistics, Applied Mathematics, Mathematical Finance, Physics, etc)
Experience in risk-modelling of trading book or banking book portfolios (model development or validation)
Experience in market risk or/and counterparty risk modelling
Experience with other risk models (Economic Capital, Stress Testing, etc.)
Strong background in Math and Probability theory - applied to finance.
Good understanding of financial products.
Good programming level in Python or R or equivalent.
Awareness of the latest technical developments in financial mathematics, pricing, and risk modelling
Up-to-date knowledge of regulatory capital requirements for market and credit risk

 

Beneficial

Experience with derivatives pricing models
Good knowledge of Data Science and Statistical inference techniques.
Modelling and pricing of financial derivatives
Computer simulations and numerical approximation methods
Experience with C++ or C# or equivalent

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